What is Speech Analytics?
Speech analytics is the processing, understanding and analysis of human speech. It can be used in live or recorded calls to gather customer information to enhance future interactions. It can also be used to monitor customer service performance. The insights gained from speech analytics can identify training opportunities for employees, thereby improving the customer experience.
How Speech Analytics Works
Speech analytics is a multi-step process. It starts with processing the raw data, which is human speech, in real-time or from a recorded interaction. Automatic speech recognition (ASR), natural language processing (NLP), machine learning and transcription are used to process and analyze this data. Once processed, speech analytics can detect keywords and sentiment, as well as redact sensitive information. A detailed report is then produced, outlining call quality, agent performance and trends.
Real-time vs Post-call Speech Analytics
Post-call speech analytics works after the fact. It can only deliver insights once a call has finished. This can be useful for a more detailed analysis of calls and for identifying common trends and issues that regularly occur.
On the other hand, real-time analytics delivers live insights during a call. This is useful for guiding agents through customer queries by detecting sentiment and keyword phrases. This can help agents who are dealing with difficult or non-standard situations and need extra support or insight to solve the customer’s issue.
Pros of Speech Analytics
Speech analytics can benefit companies in several ways by providing actionable insights from customer service calls.
Detect Trends Across Calls
Speech analytics not only uses analytics and AI to produce insights from each call, but can also detect trends. This can be helpful in spotting common issues or problems that customers face so that action can be taken to improve the experience.
Monitor Agent Performance
Monitoring customer service calls is important for ensuring a positive customer experience. Speech analytics can keep track of agent performance and analyze customer interactions to identify any weak points or training opportunities.
Improve Customer Satisfaction
Speech analytics can identify customer sentiment and offer agents live and post-call insights, which, when utilized, can improve call quality and increase your first-call resolution (FCR) rate. In turn, this gives customers a better experience and allows them to have their queries solved more quickly and efficiently.
Cons of Speech Analytics
Speech analytics can significantly improve customer service interactions. However, there can be some challenges with integrating this technology.
Potentially Poor Contextual Recognition
While speech analytics can detect keywords and phrases, the technology can’t as easily identify the context of the wider conversation. Recommendations offered to agents in live calls may sometimes be inaccurate as a result, and post-call analytics can on occasion miscategorize calls.
Difficulties in Integrating With Other Data
Speech analytics data can also have accuracy or quality issues as it can transcribe incorrectly or misunderstand context. This can then make it difficult to integrate with more reliable data sources.
Challenges to Enterprise Buy-In
Speech analytics can be costly to implement, and the technology cannot ensure 100% accuracy. Stakeholders could therefore be resistant to speech analytics as they may not see a clear ROI. This technology can also require significant changes to existing workflows, which can make employees resistant.
Use Cases for Speech Analytics
Speech analytics can be applied to several industries with specific uses and benefits in each:
- Banking and financial institutions. For financial institutions, speech analytics can detect fraud cases and ensure they are in compliance with regulations.
- Healthcare. Healthcare companies can monitor patient satisfaction and regulatory compliance, as well as identify opportunities for improvement in patient care using speech analytics.
- Emergency services. Speech analytics can help pull out necessary information from calls to deliver to emergency services and provide call handlers with important insights.
- Retail. Agents can identify sales opportunities, keep track of customer feedback and identify industry trends from speech analytics insights.
The Future of Speech Analytics
As AI and its applications continue to expand and develop, the capabilities of speech analytics are also expected to advance. This includes being able to better understand context and tone, as well as a wider understanding of different dialects and accents. These advancements can lead to greater accuracy in the transcription of calls and the insights that speech analytics systems deliver. The developments of voice first technology will also lead to an increased ROI as fewer human workers and resources will be needed for speech analytics platforms to perform correctly.
About Sutherland CX360
Sutherland CX360 is a CX intelligence platform that uses AI to analyze 100% of customer interactions, rather than the mere 3% that gets audited manually. CX360 works to analyze the customer journey, monitor quality and give you predictive outcomes.
Sutherland CX360 features:
- Rich insights into agent behaviors.
- Sentiment, topic and DSAT analysis.
- Omnichannel interaction analysis into customer expectations.
- Automated QA reports.
- Predictive models for outcomes by interaction, agent and team.
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- Blog: AI, Chatbots, Cybersecurity, the Digital Workplace and 2022
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